Using self-organising feature maps for the control of artificial organisms

Ball, N. R. and Warwick, K. (1993) Using self-organising feature maps for the control of artificial organisms. IEE Proceedings D: Control Theory and Applications, 140 (3). pp. 176-180. ISSN 0143-7054

Abstract/Summary

Variations on the standard Kohonen feature map can enable an ordering of the map state space by using only a limited subset of the complete input vector. Also it is possible to employ merely a local adaptation procedure to order the map, rather than having to rely on global variables and objectives. Such variations have been included as part of a hybrid learning system (HLS) which has arisen out of a genetic-based classifier system. In the paper a description of the modified feature map is given, which constitutes the HLSs long term memory, and results in the control of a simple maze running task are presented, thereby demonstrating the value of goal related feedback within the overall network.